University of Puerto Rico Mayagüez Campus Department of Civil Engineering and Surveying Visual Inspection of Aging Bridge Infrastructure Using Unmanned Aerial Vehicles Josie D. Bianchi Santiago, MSCE PhD Candidate in Civil Engineering IGERT Fellow NEU-UPRM
Topics Research Objective Introduction Examples of Visual Inspection Literature review Methodology Drone s Technology Pattern Recognition Technology Results Conclusions
Research Objective The objective of this project is perform the first phase of bridge inspection process, the visual inspection, in a safety and cost-effective way using unmanned aerial vehicle s, and automating the identified process of deficiencies.
Introduction The maintenance and preservation of a bridge s infrastructure is a critical objective for a bridge owner to ensure the safety of those using it. The bridge maintenance begins with visual inspection of its components, current condition, and structural flaws. Each inspection performed complies with the National Bridge Inspection Standards (NBIS) and AASHTO Manual for Bridge Evaluation (MBE).
Examples of Visual Inspection www.nde-ed.org www.terabee.com www.cras.ca
Literature Review Mitani and Matsumoto (2012), develop an efficient nondestructive highway bridge inspection methods using high definition video (HDV) digital image and Infrared (IR) thermography technologies. Heymsfield and Kuss (2014 and 2015) performed a visual bridge inspection implementing a gigapixel technology analysis. They develop high-resolution panoramic images from multiple grid images using a robotic camera mount that is enable to create interactive viewer.
Literature Review Moller (2008) develop a vertical takeoff and landing aerial vehicle to perform bridge inspections called Aerobot. Oh et al. (2008) developed a bridge inspection robot system with the aim of verify the safety status of a bridge and identified accurate data like crack width and length.
Literature Review Chen et al. (2011) use an aerial photography as a remote bridge inspection technique to supplement visual inspection. They use a small plane at altitude of 1,000 feet over the land equipped with high definition digital camera, an integrated onboard global positioning system (GPS) and highresolution optics. www.aerbrava.com
Methodology Through PRHTA database several bridge with deficiencies were identified. Three concrete bridges were chosen to perform the bridge inspection with drone s technology. After inspection, images and videos were evaluated with MatLab software tool by pattern recognition to automatic detect bridge deficiencies.
Drone s Technology DJI Phantom 3 Professional 12 megapixel photo camera including 4k video technology GPS technology Flights at a range of 1.2 miles from controller without loss communication Intelligent batteries
Pattern Recognition Technology Matlab software tool Computer Vision System Toolbox traincascadeobjectdetector vision.cascadeobjectdetector
Results The bridges are located in the highway PR-2 at Ponce, Puerto Rico
Results Bridge Inspection Process with Drones Technology
Results Pattern recognition tool Region of Interest Sets of 50 images Pattern recognition training Positive Instance Negative Instance
Results Examples of Image Recognition Tool with Bridge Spalling
Conclusions A MatLab code for concrete bridge deficiencies recognition were develop The image recognition tool needs more training to accurately recognize expected bridge deficiencies More samples to improve the recognition tool are needed The use of drones for bridge inspection is a safety and cost-effective alternative to the actual process of bridge visual inspections
Intellectual Merits and Broader Impacts This research contributed with the security of all bridgehighway users across the nation. According to the data found in this research we could reduce the cost and time of bridge inspections while preserving the safety of inspector and bridge users. The use of drones for inspecting difficult or inaccessible bridge components in a safety way represent a breakthrough in the development of inspection technologies. This benefits the government through economic and short inspections that can be repeated before the two years stipulated by the regulations, and avoid the collapse of bridges without notice.
References Agdas D. et al. (2015). Comparison of Visual Inspection and Structural-Health Monitoring As Bridge Condition Assessment Methods. Journal of Performance of Constructed Facilities, ASCE, ISSN 0887-3828/04015049(10)/$25.00. FHWA (2012). Bridge Inspector s Reference Manual (BIRM). Federal Highway Administration, National Highway Institute (HNHI-10), Arlington, Virginia 22201. FHWA NHI 12-049. Heymsfield E. and Kuss M. (2014). Implementing Gigapixel Technology in Highway Bridge Inspections. Journal of Performance of Constructed Facilities, ASCE, ISSN 0887-3828/04014074(9)/$25.00. Heymsfield E. and Kuss M. (2015). Supplementing Current Visual Highway Bridge Inspections with Gigapixel Technology. Journal of Performance of Constructed Facilities, ASCE, ISSN 0887-3828/04015015(9)/$25.00. Herrera J. (1996). Puentes. Universidad Católica de Colombia. ISBN 958-95345-03. Khan, F., Ellenberg, A., Mazzotti, M., Kontsos, A., Moon, F., Pradhan, A., & Bartoli, I. (2015). Investigation on Bridge Assessment Using Unmanned Aerial Systems. In Structures Congress 2015 (pp. 404 413). American Society of Civil Engineers. http://doi.org/doi:10.1061/9780784479117.035 MathWorks (2015). Computer Vision System Toolbox User s Guide. The MathWorks, Inc. Version 6.2 (Release R2015a). Mitani K. and Matsumoto M. (2012). Innovative Bridge Assessment Methods Using Image Processing and Infrared Thermography Technology. 37th Conference on Our World in Concrete & Structures: 29-31 August 2012. Singapore. Moller P. (2008). Caltrans Bridge Inspection Aerial Robot. Advanced Highway Maintenance and Construction Program (AHMCT). University of California at Davis, CA. Oh, J., Lee, A., Oh, S. M., Choi, Y., Yi, B., & Yang, H. W. (2008). Bridge inspection robot system with novel image processing. Bridge Maintenance, Safety, Management, Health Monitoring and Informatics Koh & Frangopol (eds). Taylor& Francis Group, London, ISBN 978-0-415-46844-2. Rens K. et al. (2005). Bridge Management and Nondestructive Evaluation. Journal of Performance of Constructed Facilities, Vol. 19, No. 1, February 1, 2005. ASCE, ISSN 0887-3828/2005/1-3 16/$25.00. Washer, G., Fenwick, R., Nelson, S., & Rumbayan, R. (2013). Guidelines for Thermographic Inspection of Concrete Bridge Components in Shaded Conditions. Transportation Research Record: Journal of the Transportation Research Board, 2360, 13 20. doi:10.3141/2360-02.
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Acknowledge This work was supported in part by the IGERT: Intelligent Diagnostics for Aging Civil Infrastructure, under the IGERT Program of the National Science Foundation (Award Number DGE-0654176) Thanks to PRHTA and engineer Francisco Padua from for their support